This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.
At a glance
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.
People who want a usable interface for interacting with AI models.
The repository reports a MIT license. Setup difficulty and device support still need to be checked upstream.
Evidence & freshness
This wider directory record has not passed catalog verification and its last sync is outside the expected refresh window.
Generally healthy automated signals, with some areas worth checking in the breakdown.
The health score is an automated maintenance signal, not a security audit or a guarantee that the tool fits your needs.
Catalog-verified records use a timestamped GitHub snapshot that passed source and completeness checks. Basic listings come from the wider automated sync and have not yet passed that stronger verification path.
Health combines recent activity, commit frequency, issue handling, contributor depth, release cadence, documentation, and community signals. Missing evidence lowers how much confidence you should place in the number.
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